Yes, you can think of it in terms of (WLOG think of any uniquely-decodable code) prefix-free codes. They're uniquely decodable - for things that are not uniquely decodable, that implies that you could put overlapping codes over that symbol. If you make a matrix like this where the rows are the bitstrings of length b and columns are individual bits:

  000 ... 000
  000 ... 001
  ...
  111 ... 110
  111 ... 111

However, you also know, for sure, that, if a prefix-free code appears in a particular row, that means since it's impossible to overlap with anything else in that row at its span. What does that imply? That the prefix-free codes have a greater 'occupancy percentage' of a single row than all other sub-bitstrings. That means that you must find fewer of them, on average, inside of a single row.

But since we know that all sub-bitstrings appear the same number of times throughout the entire matrix, what else can we deduce? That the prefix-free codes must appear /over more rows / on average, if they cannot appear as many times while looking at bit positions /along the columns/. That means they will occur as a sub-pattern in full-bitstrings more often than typical random sub-patterns.

So weakness here corresponds to the presence of patterns (prefix-free codes) that are:

- non-overlapping within bitstrings

- widely distributed across bitstrings

- due to their wide distribution, there's a higher chance of encountering these patterns in any given random file

- therefore, weak files are more compressible because they contain widely-distributed, non-overlapping patterns that compression algorithms can take advantage of